The Palestinian Economy. Theoretical and Practical Challenges

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etc.); marital status (married, separated/divorced, etc.); insurance coverage (public/private
cover), and location of residence (urban/rural). Lastly, concerning the measurement of
living standards (i.e., the ranking variable), the HCUE-2004 offers two direct measures:
total household income and total consumption expenditures. However, since the latter is
commonly advocated as a more reliable measure of households’ living standard in the
context of developing countries (Deaton and Grosh 2000), we have used this variable to
define average adjusted income per equivalent adult. This was computed – as in previous
essays – using the WHO/FAO equivalence scale proposed for the case of developing
countries (Aho, Lariviere et al. 1997; Deaton and Grosh 2000).
3.4. Estimation Methods
Measures of health care utilisation used in this study are binary variables – taking the
value of one or zero depending on whether the individual uses health care or not – and
count variables – taking non-negative integer values. Both of these variables are typically
characterised by highly skewed distributions with a non-negligible proportion of the
survey respondents reporting zero utilisation, and a very small proportion reporting
frequent utilisation far above the mean during a given period of time (O’Donnell, van
Doorslaer et al. 2007). Indeed, as in similar studies on the utilisation of health services
(e.g., van Doorslaer, Koolman et al. 2004; Morris, Sutton et al. 2005), a non-negligible
proportion of our survey respondents did not use primary-level of health care during the
relevant recall period (about 45.6%), whereas the proportions of non-users of secondaryand
tertiary-levels are even much higher (about 59% and 87% of non-users, respectively).
Clearly, features such as these make OLS estimation biased and inefficient, and call
for specific-estimation techniques (Buntin and Zaslavsky 2004). Theoretical analysis of
health care utilisation offers a variety of alternative econometric specifications (cf. e.g.,
Jones 2000; Jones and O’Donnell 2002, for a review). Among the other possible
candidates are: two-part model (TPM) (Manning, Morris et al. 1981); sample-selection
model (SSM) (Heckman 1979); hurdle model (HM) (Mullahy 1986), and finite-mixture
model (FMM) (Deb and Trivedi 2002). Many empirical studies addressed the issue of
choice between alternative econometric specifications suggest that the choice depends on
both theoretical and statistical considerations regarding health care demand. For instance,
Leung and Yu (1996) show that the SSM is susceptible to collinearity between the
inverse Mill’s ratio and the explanatory variables in the second-step equation. They
suggest using a t-test of the coefficient of the inverse Mill’s ratio to choose between the